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  2. Worked-example effect - Wikipedia

    en.wikipedia.org/wiki/Worked-example_effect

    The worked-example effect is a learning effect predicted by cognitive load theory. [1] [full citation needed] Specifically, it refers to improved learning observed when worked examples are used as part of instruction, compared to other instructional techniques such as problem-solving [2] [page needed] and discovery learning.

  3. Supervised learning - Wikipedia

    en.wikipedia.org/wiki/Supervised_learning

    A learning algorithm is biased for a particular input if, when trained on each of these data sets, it is systematically incorrect when predicting the correct output for . A learning algorithm has high variance for a particular input x {\displaystyle x} if it predicts different output values when trained on different training sets.

  4. Keras - Wikipedia

    en.wikipedia.org/wiki/Keras

    Keras is an open-source library that provides a Python interface for artificial neural networks. Keras was first independent software, then integrated into the TensorFlow library, and later supporting more. "Keras 3 is a full rewrite of Keras [and can be used] as a low-level cross-framework language to develop custom components such as layers ...

  5. Neural network (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Neural_network_(machine...

    Choice of model: This depends on the data representation and the application. Model parameters include the number, type, and connectedness of network layers, as well as the size of each and the connection type (full, pooling, etc. ). Overly complex models learn slowly. Learning algorithm: Numerous trade-offs exist between learning algorithms.

  6. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    A model may be pre-trained either to predict how the segment continues, or what is missing in the segment, given a segment from its training dataset. [48] It can be either autoregressive (i.e. predicting how the segment continues, the way GPTs do it): for example given a segment "I like to eat", the model predicts "ice cream", or "sushi".

  7. Andie MacDowell, 66, reveals the 1 word she won’t use when ...

    www.aol.com/news/andie-macdowell-66-reveals-1...

    Andie MacDowell opens up about aging and how she stays fit and healthy at 66 years old in a new interview with TODAY.com.

  8. Norovirus cases are surging. A doctor explains what to look for

    www.aol.com/news/norovirus-cases-surging-doctor...

    Infected surfaces can be cleaned with solutions containing bleach to kill the virus. In addition, be aware that there are other foodborne illnesses, too, such as E. coli, salmonella and listeria.

  9. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Sentiment of each sentence has been hand labeled as positive or negative. 3000 Text Classification, sentiment analysis 2015 [100] [101] D. Kotzias BlogFeedback Dataset Dataset to predict the number of comments a post will receive based on features of that post. Many features of each post extracted. 60,021 Text Regression 2014 [102] [103] K. Buza

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